New Developments in Unsupervised Outlier Detection Algorithms and Applications /
| Main Authors: | , , | 
|---|---|
| מחבר תאגידי: | |
| סיכום: | XXI, 277 p. 138 illus., 120 illus. in color. text | 
| שפה: | אנגלית | 
| יצא לאור: | Singapore :
          Springer Nature Singapore : Imprint: Springer,
    
        2021. | 
| מהדורה: | 1st ed. 2021. | 
| נושאים: | |
| גישה מקוונת: | https://doi.org/10.1007/978-981-15-9519-6 | 
| פורמט: | אלקטרוני ספר | 
                תוכן הענינים: 
            
                  - Overview and Contributions
- Developments in Unsupervised Outlier Detection Research
- A Fast Distance-Based Outlier Detection Technique Using A Divisive Hierarchical Clustering Algorithm
- A k-Nearest Neighbour Centroid Based Outlier Detection Method
- A Minimum Spanning Tree Clustering Inspired Outlier Detection Technique
- A k-Nearest Neighbour Spectral Clustering Based Outlier Detection Technique
- Enhancing Outlier Detection by Filtering Out Core Points and Border Points
- An Effective Boundary Point Detection Algorithm via k-Nearest Neighbours Based Centroid
- A Nearest Neighbour Classifier Based Automated On-Line Novel Visual Percept Detection Method
- Unsupervised Fraud Detection in Environmental Time Series Data. .